VideoDB Skills

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/videodb-skills

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

VideoDB Skills

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Purpose, Capabilities, Repository, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• User wants to upload and process videos from YouTube, URLs, or local files
• User needs to search for moments by speech or visual scenes
• User asks for transcription, subtitles, or subtitle styling
• User wants to edit clips — trim, combine, add text/image/audio overlays
• User needs AI-generated media (images, video, music, sound effects, voiceovers)
• User wants to transcode, change resolution, or reframe for social platforms

Operating Table

metadata.json

ORIGIN.md

SKILL.md

SKILL.md

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Step 1: Install the skill `bash npx skills add video-db/skills ### Step 2: Run setup /videodb setup The agent guides API key setup ($20 free credits, no credit card), installs the SDK, and verifies the connection.

2. Alternatively, set the API key manually: bash export VIDEODBAPI_KEY=sk-xxx ### Step 3: Install the SDK bash pip install "videodb[capture]" python-dotenv `
3. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
4. Read the overview and provenance files before loading any copied upstream support files.
5. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
6. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
7. Validate the result against the upstream expectations and the evidence you can point to in the copied files.

Imported Workflow Notes

Imported: Setup

Step 1: Install the skill

npx skills add video-db/skills

Step 2: Run setup

/videodb setup

The agent guides API key setup ($20 free credits, no credit card), installs the SDK, and verifies the connection.

Alternatively, set the API key manually:

export VIDEO_DB_API_KEY=sk-xxx

Step 3: Install the SDK

pip install "videodb[capture]" python-dotenv

Imported: Purpose

The only video skill your agent needs. Upload any video, connect real-time streams, search inside by what was said or shown, build complex editing workflows with overlays, generate AI media, add subtitles, and get instant streaming links — all via the VideoDB Python SDK.

Examples

Example 1: Ask for the upstream workflow directly

Use @videodb-skills to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @videodb-skills against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @videodb-skills for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @videodb-skills using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: Examples

Upload and transcribe:

"Upload https://www.youtube.com/watch?v=FgrO9ADPZSA and give me a transcript"

Search across videos:

"Search for 'product demo' in my latest video"

Add subtitles:

"Add subtitles with white text on black background"

Multi-clip editing:

"Take clips from 10s-30s and 45s-60s, add a title card, and combine them"

AI media generation:

"Generate background music and overlay it on my video"

Real-time capture:

"Capture my screen and transcribe it in real-time"

Reframe for social:

"Convert this to vertical for Instagram Reels"

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/videodb-skills

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @trpc-fullstack

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @trust-calibrator

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @turborepo-caching

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @tutorial-engineer

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/n/a

examples

examples/n/a

scripts

scripts/n/a

agents

agents/n/a

assets

assets/n/a

Imported Reference Notes

Imported: Capabilities

Imported: Repository

https://github.com/video-db/skills

Version: 1.1.0 Maintained By: VideoDB

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.